A. Onofre

113.9k total citations
52 papers, 480 citations indexed

About

A. Onofre is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Computer Networks and Communications. According to data from OpenAlex, A. Onofre has authored 52 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Nuclear and High Energy Physics, 10 papers in Astronomy and Astrophysics and 4 papers in Computer Networks and Communications. Recurrent topics in A. Onofre's work include Particle physics theoretical and experimental studies (37 papers), Quantum Chromodynamics and Particle Interactions (20 papers) and High-Energy Particle Collisions Research (17 papers). A. Onofre is often cited by papers focused on Particle physics theoretical and experimental studies (37 papers), Quantum Chromodynamics and Particle Interactions (20 papers) and High-Energy Particle Collisions Research (17 papers). A. Onofre collaborates with scholars based in Portugal, United States and Spain. A. Onofre's co-authors include J. A. Aguilar–Saavedra, N. F. Castro, M. C. N. Fiolhais, F. Veloso, J. Carvalho, Rui Santos, R. Gonçalo, José A. Font, G. Aad and E. D. Mendes Gouveia and has published in prestigious journals such as Journal of High Energy Physics, Physical review. D and Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment.

In The Last Decade

A. Onofre

43 papers receiving 469 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
A. Onofre Portugal 14 416 88 26 23 19 52 480
M. Pimenta Portugal 13 345 0.8× 85 1.0× 24 0.9× 70 3.0× 19 1.0× 84 416
К. Г. Компаниец Russia 10 418 1.0× 85 1.0× 10 0.4× 68 3.0× 21 1.1× 113 490
A. Haungs Germany 11 324 0.8× 130 1.5× 18 0.7× 44 1.9× 14 0.7× 82 356
L. Nellen Mexico 9 340 0.8× 149 1.7× 17 0.7× 14 0.6× 9 0.5× 24 394
M. Boezio Italy 9 296 0.7× 320 3.6× 14 0.5× 23 1.0× 41 2.2× 48 456
S. C. Tonwar India 13 516 1.2× 147 1.7× 22 0.8× 41 1.8× 5 0.3× 71 565
S. J. Stochaj United States 8 287 0.7× 182 2.1× 14 0.5× 18 0.8× 6 0.3× 20 358
J. R. Cudell Belgium 17 872 2.1× 131 1.5× 13 0.5× 10 0.4× 18 0.9× 66 928
T. Yoshida Japan 8 294 0.7× 334 3.8× 14 0.5× 15 0.7× 21 1.1× 44 402
J. Zweizig United States 10 303 0.7× 51 0.6× 15 0.6× 3 0.1× 13 0.7× 24 358

Countries citing papers authored by A. Onofre

Since Specialization
Citations

This map shows the geographic impact of A. Onofre's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by A. Onofre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Onofre more than expected).

Fields of papers citing papers by A. Onofre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. Onofre. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by A. Onofre. The network helps show where A. Onofre may publish in the future.

Co-authorship network of co-authors of A. Onofre

This figure shows the co-authorship network connecting the top 25 collaborators of A. Onofre. A scholar is included among the top collaborators of A. Onofre based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with A. Onofre. A. Onofre is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Freitas, O., et al.. (2024). Comparison of neural network architectures for feature extraction from binary black hole merger waveforms. Machine Learning Science and Technology. 5(1). 15036–15036. 2 indexed citations
2.
Herdeiro, Carlos, A. Morais, A. Onofre, et al.. (2024). Generating gravitational waveform libraries of exotic compact binaries with deep learning. Physical review. D. 109(12). 1 indexed citations
3.
Freitas, O., et al.. (2024). Deep-learning classification and parameter inference of rotational core-collapse supernovae. Physical review. D. 110(6). 1 indexed citations
4.
Aad, G., et al.. (2023). Search for dark photons from Higgs boson decays via ZH production with a photon plus missing transverse momentum signature from pp collisions at √s = 13 TeV with the ATLAS detector. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2 indexed citations
5.
Aad, G., et al.. (2023). Search for Majorana neutrinos in same-sign WW scattering events from pp collisions at √s=13 TeV. RepositóriUM (Universidade do Minho).
6.
Morais, A., et al.. (2023). Exploring mixed lepton-quark interactions in non-resonant leptoquark production at the LHC. Journal of High Energy Physics. 2023(11). 3 indexed citations
7.
Ferreira, P. M., et al.. (2023). Collider phenomenology of new neutral scalars in a flavored multi-Higgs model. Physical review. D. 107(9).
8.
Onofre, A., et al.. (2023). Search for an invisible scalar in $$ t\overline{t} $$ final states at the LHC. Journal of High Energy Physics. 2023(11).
9.
Morais, A., et al.. (2023). Deep learning searches for vector-like leptons at the LHC and electron/muon colliders. The European Physical Journal C. 83(3). 6 indexed citations
10.
Gonçalves, Gonçalo, et al.. (2023). Machine-learning Love: classifying the equation of state of neutron stars with transformers. Journal of Cosmology and Astroparticle Physics. 2023(12). 1–1. 5 indexed citations
11.
Aad, G., et al.. (2022). Search for heavy particles in the b-tagged dijet mass distribution with additional b-tagged jets in proton-proton collisions at p root s=13 TeV with the ATLAS experiment. RepositóriUM (Universidade do Minho). 3 indexed citations
12.
Aad, G., et al.. (2022). University of Birmingham Research Portal (University of Birmingham). 10 indexed citations
13.
Gouveia, E. D. Mendes, et al.. (2021). Light Higgs searches in tt¯ ϕ production at the LHC. Repositório Científico do Instituto Politécnico de Lisboa (Instituto Politécnico de Lisboa). 6 indexed citations
14.
Herdeiro, Carlos, A. Morais, A. Onofre, et al.. (2021). Ultralight bosons for strong gravity applications from simple Standard Model extensions. Journal of Cosmology and Astroparticle Physics. 2021(12). 47–47. 23 indexed citations
15.
Onofre, A., et al.. (2020). Scalar mass dependence of angular variables in $t\\bar tφ$ production. Repositório Científico do Instituto Politécnico de Lisboa (Instituto Politécnico de Lisboa). 5 indexed citations
16.
Ferroglia, Andrea, M. C. N. Fiolhais, E. D. Mendes Gouveia, & A. Onofre. (2019). Role of the tt¯h rest frame in direct top-quark Yukawa coupling measurements. Physical review. D. 100(7). 9 indexed citations
17.
Fiolhais, M. C. N., Rikkert Frederix, R. Gonçalo, et al.. (2017). Probing the CP nature of the Higgs coupling in tt¯h events at the LHC. Physical review. D. 96(1). 24 indexed citations
18.
Castro, N. F., et al.. (2014). Studying theWtbvertex structure using recent LHC results. Physical review. D. Particles, fields, gravitation, and cosmology. 90(11). 16 indexed citations
19.
Ferreira, P. M., et al.. (2009). Dimension six flavor changing neutral current operators and top-quark production at the LHC. Physical review. D. Particles, fields, gravitation, and cosmology. 79(1). 27 indexed citations
20.
Onofre, A.. (2006). International Workshop on Top Quark Physics. CERN Document Server (European Organization for Nuclear Research). 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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